FARE - Factor Relationship weighting method

Overview

FARE uses a one-directional factor relationship matrix - each row is filled independently (not required to be reciprocal). Row sums are normalised to weights. Simpler than AHP (no eigenvalue computation, no consistency check) but less rigorous.

Output

Weight, higher is better

Data

Crisp, complete numeric matrix

Weights

Derived internally, no weight source needed

Size

2+ alternatives, 3-12 criteria works best

Used for

Any (objective weighting)

How it works

1. 1

   Sum each row of the relation matrix to get S_i = Σ_j f_{ij}. Normalise: w_i = S_i / Σ_k S_k.

   $$S_i=\sum _{j=1}^n{f}_{ij};w_i=\frac{S_i}{{\sum }_{k=1}^n{S}_k}$$

   Žižović et al. 2020, p.1101 Eqs.(1)-(2) (pending PDF page verification)

Look elsewhere when

Assumptions to verify

• Decision matrix exists with measurable criteria
• Sufficient inter-alternative variation per criterion

Edge cases and pitfalls

• Not requiring reciprocity means inconsistency can go undetected - always inspect row sums for reasonableness.

Works with

How to cite